Robust Statistical Procedures

Robust Statistical Procedures

by Peter J. Huber
     
 

Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in…  See more details below

Overview

Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition. This book provides a quick introduction to robustness. Graduate and undergraduate students in statistics will find it especially useful. Peter J. Huber is Professor of Statistics at the University of Bayreuth in Germany.
— Vickie Kearn (kearn@siam.org), the Publisher

Editorial Reviews

American Mathematical Monthly
Brief, well-organized introduction and overview of robust statistics. This edition adds a chapter on recent developments and updates the list of references.

Product Details

ISBN-13:
9780898710243
Publisher:
SIAM
Publication date:
11/28/1977
Series:
Cbms-NSF Regional Conference Series in A
Pages:
56
Product dimensions:
5.91(w) x 9.06(h) x (d)

What People are saying about this

C. Bouza
I highly recommend this book for a first course in robust statistics for students of mathematical statistics.
— Investigacion Operacional

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